It is well known that a light beam can be varied in intensity to produce a signal containing information within the amplitude modulation. Furthermore, telecommunications systems rely upon modulating the wavelengths of the light signals in fiber optics, to impart data onto the light beam. Furthermore, it has been shown that a fluorescent light source can be used as a one-way communications device (Dachs, U.S. Pat. No. 3,900,404, Aug. 19, 1975) for voice communications using an external modulated signal imparted upon the lamp's AC current in an amplitude modulation scheme.
The inherent weakness in this system (Dachs) is the fact that the observed light flickers as a function of the audio signal's intensity. For many applications, this is an unacceptable solution. Subsequent publications and inventions have conceived different modulation techniques such as pulse code modulation and timing modulation and have adapted the encoding techniques for applications that require greater data bandwidths with mixed data types (Leeb, et al., U.S. Pat. No. 6,794,831, Sep. 21, 2004); however, these designs are complex and require a greater amount of power, circuitry, and cost to accomplish.
Hearing impaired people lose their ability to distinguish speech signal in ambient noise since the human hearing system is sensitive to interfering noise. Interfering noise decreases the quality and intelligibility of the speech signal. Speech enhancement techniques use signal processing to reduce the noise and improve the perceptual quality and intelligibility of the speech signal. However, these techniques are generally ineffective when the noise also consists of speech as it is difficult to distinguish between the desired speech signal and the undesired speech, which is considered to be noise.
Beamforming is a common technique of spatial filtering used for enhancing speech coming from a prescribed direction while eliminating noise (including speech) coming from other directions, relative to how they arrive at the microphone array embedded in the hearing aid(s). Beamforming technology does this by creating a constructive interference pattern (i.e., focus) in a particular direction and destructive interference pattern (i.e., null) in other directions. A beamforming microphone array can thereby be used to take advantage of some combination of spatial, temporal and spectral information to create a beam to “listen” in a desired direction. Beamforming approaches can be fixed, with a beam electronically steered in a predetermined fixed direction (usually normal to the line or plane of the microphone array's microphone elements), or electronically-steerable by allowing the electronic steering of the beam in a desired direction, upon demand. (Of course, mechanically re-orienting a fixed array will also effectively change its steering.) Beamforming is performed in devices such as hearing aids to enhance the signal-to-noise ratio (SNR) of the desired speech source and, in doing so, to increase the speech intelligibility by the user of the hearing aids based on the characteristic ability of the human auditory system to recognize signals (sounds) that are higher than the background (ambient) noise.
Prior art directional beamforming solutions are dependent upon the listener physically looking at a target to obtain maximum amplification; for example, fixed beamform hearing aids. A speech source, whether associated with a human talker or mechanical transducer, does not represent an ideal, spherical radiator. In the case of a room-size, near-field environment, any realistic source possesses a clear degree of directionality and spatial attenuation. This implies that a sensor that is facing the talker will tend to receive a stronger signal than sensors located to the side or physically behind the source. There are many instances where a participant in a conversation may not be actively looking at other participants. Accordingly, prior art solutions exhibit a number of flaws that hamper the hearing impaired to use these self-contained microphone array devices. These include poor performance amid background noise and low sensitivity at low frequencies. This is an intricate problem due the existence of several sources of error, such as periodicity in correlated signals and coherent noise or multi-path due to reverberation, and misidentification of desired source signals. Some prior art solutions, in an attempt to compensate for this issue, use an adaptive approach where they operate somewhat independently of the mechanical pointing and instead try to identify noise source and location and steer nulls toward them. Such prior art solutions, however, are not effective for wearable devices.
The pressure and velocity of a homogeneous acoustic field are governed by the Helmholtz equations. Any spatial wave field can also be described using the solutions to these equations. One approach to solving the acoustic wave equation is based on the pressure and its normal derivatives at a boundary. Green's second identity is applied to the homogeneous acoustic wave Helmholtz's equation to obtain the Helmholtz Integral Equation. The Green's Function represents an impulse response to an inhomogeneous differential equation. For a spatially constrained source located at a particular location (i.e., a point source in space), the Green's Function represents the transfer function of the acoustic channel between the source and any other location in space, as well as provides for boundary conditions (e.g. the location and other properties of walls, floor, and ceiling of an interior room), thereby modeling both the physical and geometrical properties of the acoustic environment. Optimally estimating the one or more Green's Functions of an acoustic environment and the sound capture system that receives the audio input allows the reconstruction of the one or more original sounds that emanate from point sources in various locations in the environment. Green's Function processing thereby allows separation of acoustic sources in real environments with fewer microphones than other spatial processing methods, such as beamforming.
Through applied effort, ingenuity, and innovation, Applicant has identified a number of deficiencies and problems with distinguishing speech signals in an ambient noise environment where the need exists for better methods to separate a speech or sound source and communicate that information. Applicant has developed a solution that is embodied by the present invention, which is described in detail below.